scripts/Fine-tune_RLIP-ParSeD_VCOCO.sh
python models/ops/setup.py build install;
pip install -I transformers==4.5.1 --no-cache-dir --force-reinstall
pip install -r requirements_ParSeDETRHOI.txt;
pip install pkgs/pycocotools-2.0.2.tar.gz;
pip install submitit==1.3.0;
pip install timm;
# export NCCL_DEBUG=INFO;
# export NCCL_IB_HCA=mlx5;
# export NCCL_IB_TC=136;
# export NCCL_IB_SL=5;
# export NCCL_IB_GID_INDEX=3;
# export TORCH_DISTRIBUTED_DETAIL=DEBUG;
# python -m torch.distributed.launch --nproc_per_node=8 --nnodes=$WORLD_SIZE --node_rank=$RANK \
#     --master_addr=$MASTER_ADDR --master_port=$MASTER_PORT --use_env main.py \
python -m torch.distributed.launch --nproc_per_node=1 --use_env main.py \
    --pretrained /PATH/TO/params/ParSeD_CEFocal_BiasT_Freq500_PseuEuc03_COCO_bs128_50e_checkpoint0049.pth \
    --output_dir /PATH/TO/logs/ParSeD_VCOCO_WordsV3_Freq500_GIoUVb_PseuEuc03_COCO_bs128_50e_60e \
    --dim_feedforward 1024 \
    --epochs 60 \
    --lr_drop 40 \
    --num_queries 200 \
    --enc_layers 6 \
    --dec_layers 3 \
    --dataset_file vcoco \
    --hoi_path /mnt/data-nas/peizhi/data/v-coco \
    --num_obj_classes 81 \
    --num_verb_classes 29 \
    --hoi \
    --backbone resnet50 \
    --set_cost_bbox 2.5 \
    --set_cost_giou 1 \
    --bbox_loss_coef 2.5 \
    --giou_loss_coef 1 \
    --num_workers 4 \
    --batch_size 4 \
    --num_feature_levels 4 \
    --with_box_refine \
    --use_nms_filter \
    --load_backbone supervised \
    --lr 1e-4 \
    --lr_backbone 1e-5 \
    --text_encoder_lr 1e-5 \
    --RLIP_ParSeD \
    --use_no_obj_token \
    --obj_loss_type cross_entropy \
    --verb_loss_type focal \
    --save_ckp \
    --schedule step \
    --sampling_stategy freq \
    # --giou_verb_label \
